Challenges for Updating 3D Cadastral Objects using LiDAR and Image-based Point Clouds

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Abstract

Nowadays due to the increasing complex and multifunctional building environment in the urban areas it is required an accurate geometry and proper legal registration of the cadastral objects including third dimension and time aspect. 2D land-parcel data seems insufficient to address the variety of problems in high density residential areas. This fact motivates scientists worldwide to work on 3D Cadastral Data models for representation of 3D legal and physical
information. Third dimension is important in cases of space subdivision with different owners and used for various purposes which requires its accurate registration. However, it is of great importance to maintain the 3D information up to date. With the rapid development in the fields of photogrammetry, laser scanning and computer vision high accurate 3D data can be obtained. However, numerous challenges appear while processing, storing, transferring and visualizing. Currently, efficient management of “big data” is widely discussed. In this respect developed algorithms in support of automatization of data processing, segmentation and visualization can be very helpful. Current paper focuses on usage of photogrammetric data for updating 3D information. More specifically, we investigate the opportunities for updating 3D cadastral objects using precise multi epoch airborne laser scanning 3D data, point clouds derived from high resolution imagery from dense matching algorithms and maps used to provide semantic information about the land cover class and 2D special information of the boundary of the cadastral objects. In the paper we describe the type and size of uncertainties when updating 3D cadastral models. This includes the uncertainty of the initial model, caused by inaccuracies in the measurements when building the initial models. Next, a careful registration with the newly acquired dataset is necessary in order to better describe changes of objects, instead of changes in datasets. The benefits of the fourth dimension in cadastral information systems are also discussed in the paper. Different methods for detecting changes in time using airborne laser scanning (ALS) data have been used for various application such as map updating (Vosselman, et al, 2004), evaluation of damages as a result from a physical disasters (Murakami et al, 1999) etc. Usually change detection is done by segmentation, classification or implementation of specific mapping rules. In our paper we focus on detecting changes while comparing ALS dataset from different epochs and between point clouds obtained from ALS and high resolution images for same territory. We also discuss the difficulties in detecting changes for different types of 3D cadastral objects. The analysis is done for a common dataset located in Netherlands. In conclusion the opportunities of using high accurate point cloud data for keeping up to date 3D cadastral systems are presented and the challenges and problems are shown.
Original languageEnglish
Title of host publicationProceedings 5th International Workshop on 3D Cadastres
Subtitle of host publication18-20 October 2016, Athens, Greece
EditorsPeter van Oosterom, Efi Dimopoulou, Elfriede Fendel
Place of PublicationCopenhagen
PublisherInternational Federation of Surveyors (FIG)
Pages169-182
ISBN (Electronic)978-87-92853-49-3
ISBN (Print)978-87-92853-47-9
Publication statusPublished - 18 Oct 2016
Event5th International FIG Workshop on 3D Cadastres 2016 - Athens, Greece
Duration: 18 Oct 201620 Oct 2016
http://www.gdmc.nl/3dcadastres/workshop2016/

Conference

Conference5th International FIG Workshop on 3D Cadastres 2016
CountryGreece
CityAthens
Period18/10/1620/10/16
Internet address

Fingerprint

laser
segmentation
computer vision
image resolution
photogrammetry
visualization
disaster
land cover
imagery
information system
urban area
geometry
damage
registration

Keywords

  • METIS-321348

Cite this

Koeva, M., & Oude Elberink, S. (2016). Challenges for Updating 3D Cadastral Objects using LiDAR and Image-based Point Clouds. In P. van Oosterom, E. Dimopoulou, & E. Fendel (Eds.), Proceedings 5th International Workshop on 3D Cadastres: 18-20 October 2016, Athens, Greece (pp. 169-182). Copenhagen: International Federation of Surveyors (FIG).
Koeva, Mila ; Oude Elberink, Sander. / Challenges for Updating 3D Cadastral Objects using LiDAR and Image-based Point Clouds. Proceedings 5th International Workshop on 3D Cadastres: 18-20 October 2016, Athens, Greece. editor / Peter van Oosterom ; Efi Dimopoulou ; Elfriede Fendel. Copenhagen : International Federation of Surveyors (FIG), 2016. pp. 169-182
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keywords = "METIS-321348",
author = "Mila Koeva and {Oude Elberink}, Sander",
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Koeva, M & Oude Elberink, S 2016, Challenges for Updating 3D Cadastral Objects using LiDAR and Image-based Point Clouds. in P van Oosterom, E Dimopoulou & E Fendel (eds), Proceedings 5th International Workshop on 3D Cadastres: 18-20 October 2016, Athens, Greece. International Federation of Surveyors (FIG), Copenhagen, pp. 169-182, 5th International FIG Workshop on 3D Cadastres 2016, Athens, Greece, 18/10/16.

Challenges for Updating 3D Cadastral Objects using LiDAR and Image-based Point Clouds. / Koeva, Mila; Oude Elberink, Sander.

Proceedings 5th International Workshop on 3D Cadastres: 18-20 October 2016, Athens, Greece. ed. / Peter van Oosterom; Efi Dimopoulou; Elfriede Fendel. Copenhagen : International Federation of Surveyors (FIG), 2016. p. 169-182.

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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T1 - Challenges for Updating 3D Cadastral Objects using LiDAR and Image-based Point Clouds

AU - Koeva, Mila

AU - Oude Elberink, Sander

PY - 2016/10/18

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N2 - Nowadays due to the increasing complex and multifunctional building environment in the urban areas it is required an accurate geometry and proper legal registration of the cadastral objects including third dimension and time aspect. 2D land-parcel data seems insufficient to address the variety of problems in high density residential areas. This fact motivates scientists worldwide to work on 3D Cadastral Data models for representation of 3D legal and physicalinformation. Third dimension is important in cases of space subdivision with different owners and used for various purposes which requires its accurate registration. However, it is of great importance to maintain the 3D information up to date. With the rapid development in the fields of photogrammetry, laser scanning and computer vision high accurate 3D data can be obtained. However, numerous challenges appear while processing, storing, transferring and visualizing. Currently, efficient management of “big data” is widely discussed. In this respect developed algorithms in support of automatization of data processing, segmentation and visualization can be very helpful. Current paper focuses on usage of photogrammetric data for updating 3D information. More specifically, we investigate the opportunities for updating 3D cadastral objects using precise multi epoch airborne laser scanning 3D data, point clouds derived from high resolution imagery from dense matching algorithms and maps used to provide semantic information about the land cover class and 2D special information of the boundary of the cadastral objects. In the paper we describe the type and size of uncertainties when updating 3D cadastral models. This includes the uncertainty of the initial model, caused by inaccuracies in the measurements when building the initial models. Next, a careful registration with the newly acquired dataset is necessary in order to better describe changes of objects, instead of changes in datasets. The benefits of the fourth dimension in cadastral information systems are also discussed in the paper. Different methods for detecting changes in time using airborne laser scanning (ALS) data have been used for various application such as map updating (Vosselman, et al, 2004), evaluation of damages as a result from a physical disasters (Murakami et al, 1999) etc. Usually change detection is done by segmentation, classification or implementation of specific mapping rules. In our paper we focus on detecting changes while comparing ALS dataset from different epochs and between point clouds obtained from ALS and high resolution images for same territory. We also discuss the difficulties in detecting changes for different types of 3D cadastral objects. The analysis is done for a common dataset located in Netherlands. In conclusion the opportunities of using high accurate point cloud data for keeping up to date 3D cadastral systems are presented and the challenges and problems are shown.

AB - Nowadays due to the increasing complex and multifunctional building environment in the urban areas it is required an accurate geometry and proper legal registration of the cadastral objects including third dimension and time aspect. 2D land-parcel data seems insufficient to address the variety of problems in high density residential areas. This fact motivates scientists worldwide to work on 3D Cadastral Data models for representation of 3D legal and physicalinformation. Third dimension is important in cases of space subdivision with different owners and used for various purposes which requires its accurate registration. However, it is of great importance to maintain the 3D information up to date. With the rapid development in the fields of photogrammetry, laser scanning and computer vision high accurate 3D data can be obtained. However, numerous challenges appear while processing, storing, transferring and visualizing. Currently, efficient management of “big data” is widely discussed. In this respect developed algorithms in support of automatization of data processing, segmentation and visualization can be very helpful. Current paper focuses on usage of photogrammetric data for updating 3D information. More specifically, we investigate the opportunities for updating 3D cadastral objects using precise multi epoch airborne laser scanning 3D data, point clouds derived from high resolution imagery from dense matching algorithms and maps used to provide semantic information about the land cover class and 2D special information of the boundary of the cadastral objects. In the paper we describe the type and size of uncertainties when updating 3D cadastral models. This includes the uncertainty of the initial model, caused by inaccuracies in the measurements when building the initial models. Next, a careful registration with the newly acquired dataset is necessary in order to better describe changes of objects, instead of changes in datasets. The benefits of the fourth dimension in cadastral information systems are also discussed in the paper. Different methods for detecting changes in time using airborne laser scanning (ALS) data have been used for various application such as map updating (Vosselman, et al, 2004), evaluation of damages as a result from a physical disasters (Murakami et al, 1999) etc. Usually change detection is done by segmentation, classification or implementation of specific mapping rules. In our paper we focus on detecting changes while comparing ALS dataset from different epochs and between point clouds obtained from ALS and high resolution images for same territory. We also discuss the difficulties in detecting changes for different types of 3D cadastral objects. The analysis is done for a common dataset located in Netherlands. In conclusion the opportunities of using high accurate point cloud data for keeping up to date 3D cadastral systems are presented and the challenges and problems are shown.

KW - METIS-321348

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BT - Proceedings 5th International Workshop on 3D Cadastres

A2 - van Oosterom, Peter

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Koeva M, Oude Elberink S. Challenges for Updating 3D Cadastral Objects using LiDAR and Image-based Point Clouds. In van Oosterom P, Dimopoulou E, Fendel E, editors, Proceedings 5th International Workshop on 3D Cadastres: 18-20 October 2016, Athens, Greece. Copenhagen: International Federation of Surveyors (FIG). 2016. p. 169-182